1. Field of the Invention
The invention relates to video preprocessing systems in general, and more particularly, to a video preprocessor employed for discriminating a target image from background on the basis of mass intensity contrast and relative motion using discrete gray level values as a measure of video content.
2. Description of the Prior Art
An example of a system employing a video preprocessor is a video tracking system which typically comprises a video tracker, control servo electronics, a gimballed pointing mechanism, and an electro-optical sensor. In general, the electro-optical sensor which is usually a TV camera is mounted directly to and boresighted with the gimbal mechanism and transmits electrical data in a standard video frame format corresponding to its field of view to the video tracker at a frequency on the order of 30 to 60 times a second. The video tracker may append the video frame signals to include identification cursors which may be used to define a point or an area of the video frame signal. The combined video signals are sent to a TV monitor for displaying the intensity pattern of the field of view to an operator. An operator generally may interact with the video tracker by controlling the position of the cursors on the TV screen in an attempt to define the position of the target. Once the operator has pinpointed the target or enclosed the target in an area defined by the cursors, video tracking or "lock-on" of the target may be initiated. The basic functions of a video tracker are to discriminate a target image from the background in the field of view represented by the standard video signal frame data and compute error signals based on the change in position and velocity of the potential target image. These error signals are used as command signals to the control servos which in turn control the positioning of the gimballed mechanism altering the field of view of the TV sensor in such a direction to maintain the target within a specified area in the field of view.
Normally, the video trackers employ a video preprocessor for providing target discrimination from the video frame signals which represent the field of view of the TV sensor. Some preprocessors such as that disclosed in U.S. Pat. No. 3,865,974 issued to Fredrick C. Alpers on Feb. 11, 1975, and U.S. Pat. No. 3,341,653 issued to J. R. Kruse, Jr. on Sept. 12, 1967 define a target according to the sampled gray level of a selected spot or point on the screen of the TV monitor. In both of these systems, the sampled particular gray level is declared as the potential target and tracking is performed by following the gray level spot around the field of view. No attempt is made in these systems to assign other gray level values to the target or to assign gray levels to the background and no mechanism is provided for eliminating residual background. It is evident that these type systems discriminate only a very small portion of the target image in most cases, and that there exists a high probability that "lock-up" may occur on background, if background has the same gray level as the sampled gray level declared as the target. Alpers further includes a time dependent coordinate function as an additional measurement dimension in discriminating the target. However, since no mechanism is provided for eliminating residual background gray levels, then the tracking system may still "lock-on" to a gray level of the background which falls in close proximity to the time dependent coordinate of the gray level spot declared on the target.
Other preprocessors, such as those disclosed in U.S. Pat. No. 3,562,423 issued to Murphy on Feb. 9, 1971; U.S. Pat. No. 3,586,770 issued to Bonebreak et al on June 22, 1971; and U.S. Pat. No. 3,829,614 issued to Ahlbom et al on Aug. 13, 1974, declare a target based on a band of gray levels selected from the intensity pattern of the field of view of the sensor. Murphy, for example, has adjustable upper and lower gray level values which define a band of gray levels. The preprocessor, in this case, then declares a target by gating only those video signals within a field of regard which have gray levels falling within the defined band of gray levels. Bonebreak also identifies a potential target as those gray levels within a field of regard which fall within an adjustable gray level band. In this system, an operator interacts with the preprocessor to pinpoint a target on the TV screen as the crosspoint of coordinate cursors. The preprocessor searches in a small surrounding region about the crosspoint for the lowest and highest gray levels and assigns those gray levels falling therebetween to a target set. Ahlbom et al teaches still another preprocessor which identifies a target based on a band of gray levels. This preprocessor computes an average gray level value which is used to center the gray level band and to adaptively set upper and lower gray level quantity limits based on feedback correlation information.
All of these type preprocessor systems, in identifying a target image based on a band of gray levels, may also include as the target portions of the background which have gray levels based on the same gray level band. There is no reason to believe, except in an exceptional case, that only the target has these gray levels defined by the gray level band. There are no provisions made for discriminating a target set from a background set based on disjoint set of gray levels, nor is there provided any mechanism for eliminating residual background. In Murphy, the operator must make the decisions of where to set the upper and lower levels of the gray level bands and once set, these remain fixed.
Another preprocessor, such as that disclosed by Jonsson in U.S. Pat. No. 3,745,244 issued July 10, 1973, segregates a portion of the field of view of the sensor into inner and outer windows enclosing a predetermined target image. The average gray level value of the outer window is computed and is representative as the mean intensity of the background. Light and dark intensities relative to the mean intensity are identified in the inner target window and the gray level intensity which has the largest area is declared the target and submitted to the video tracker for tracking purposes. It is understood that during the averaging process, it is possible to lose quite a bit of information of the intensity pattern structure of the field of view. Pieces of the target may occur in the background and vice versa, thus the computed mean is not considered the best statistic for discriminating target images. In order for this type of preprocessor to function effectively, the target image must have a dominant contrast with the background or the background requires some structure. Otherwise, it is possible to just discriminate background and not the target at all or just select small regions of the target. This type preprocessor appears to guarantee target image discrimination only for the simple condition in which the target is contrasted on a uniform background.
Still another preprocessor is disclosed in U.S. Pat. No. 3,903,357 by Woolfson et al issued Sept. 2, 1975. This preprocessor identifies a target by a number of track windows which define the center and outer edges of a potential target by basically considering contrasting edges of gray level intensity patterns. As is the case in the Woolfson preprocessor described here and in some of the other preprocessors described above which are all essentially based on computing averages, the assumption is made that the intensity pattern of the field of view does not change dynamically. Thus, conditions which create the intensity gray levels which define the sizes and shapes of the images in the field of view are assumed to vary slowly compared to the frequency at which computations are made. This may be fine for some applications, but when dealing with a highly dynamic environment like trying to capture a missle or higg velocity aircraft in flight, the changes in target image are very frequent and very extensive and dramatic. These systems which require accumulation of data and averaging to make decisions normally cannot respond functionally to rapidly changing intensity pattern conditions. In some instances, it is possible that a target contrast image will flip instantaneously. Most systems usually "lock-on" to background when a target goes through an instant contrast change. It appears that in order for these systems to function effectively the intensity pattern of the field of view may not change faster than the time required to make data computations.
In addition, these preprocessors which have been briefly described above mainly function to interface with simple video centroidal trackers which normally define tracking errors based on effective areas of gray level signals which cross a threshold in a predetermined region. The centroidal type tracker generally functions on a pure black and white pattern and is unable to function with gray level image patterns because of a normalization constant which it is unable to derive easily or effectively with the tracking method it uses. Thus, the preprocessor employed thereby is required to convert everything into a black and white image which is normalized based on the area of a track window. These preprocessors are not required to derive amplitude structure of the image which they declare as the target, so they derive patterns which have no amplitude structure, that is patterns based on either a one or a zero.
Other preprocessers, such as those which are employed by a digital correlation type video tracker, need more precision in defining a target image. A preprocessor suitable for this purpose must preserve more of the character of the image than just a binary 0 and 1. The present invention is believed to provide a precise definition of a target image suitable for use in a digital correlation tracker and equivalent system plus provide an additional dimension of measurement for target discrimination not believed found in the present video tracking systems.